Investigation of Fuel Economy Prediction Technology Considering Engine Thermal Flow for Hybrid Electric Vehicle, and Application to Vehicle Development Process 2024-01-2408
Powertrain development requires an efficient development process with no rework and model-based development (MBD). In addition, to performance design that achieves low CO2 emissions is also required. Furthermore, it also demands fuel economy performance considering real-world usage conditions, and in North America, the EPA (U.S. Environmental Protection Agency) 5-cycle, which evaluates performance in a combination of various environments, is applied. This evaluation mode necessitates predicting performance while considering engine heat flow. Particularly, simulation technology that considers behavior based on engine temperature for Hybrid Electric Vehicle (HEV) is necessary.
Additionally, in the development trend of vehicle aerodynamic improvement, variable devices like Active Grille Shutter (AGS) are utilized to contribute to reducing CO2 emissions. When equipped with AGS, the engine's heat flow environment also changes, resulting in more complex phenomena in the engine compartment compared to the without AGS. As described above, simulation technology that consider behavior based on engine temperature and the behavior of aerodynamic improvement devices are crucial for identifying trade-offs in vehicle performance.
In this study, after clarifying the functions and models required to predict the fuel economy of the EPA 5-cycle, an engine thermal plant have been constructed and coupled with vehicle simulation. The vehicle simulation achieved highly accurate EPA 5-cycle fuel economy prediction. Furthermore, a conceptual-level Co-Simulation environment, suitable for early-stage development was utilized to study performance requirements. This was followed by transitioning to a detailed-level Co-Simulation environment that meets the necessary specifications during the mid-term of development. The conceptual-level Co-Simulation environment allows for clarifying the performance requirements of each device in the early stages of development. The detailed-level Co-Simulation environment enables optimization control after determining the hardware specifications in the mid-term of development.
